Utility grade wind turbines (i.e., wind turbines designed to provide electrical power to a utility grid) can have large rotors (e.g., 30 or more meters in diameter). Asymmetric loading across these rotors occurs due to vertical and horizontal wind shears, yaw misalignment and turbulence. These asymmetric loads contribute to extreme loads and the quantity of fatigue cycles on the rotor blades and other wind turbine components.
As a result of these extreme loads and fatigue cycles, components of the wind turbines have a limited useful life and must be replaced. The condition of various wind turbine components are currently monitored using sensors designed for condition monitoring. Techniques and devices used for monitoring of wind turbine components are generally referred to a “condition-based monitoring” (CBM) techniques and devices. An overview of CBM techniques can be found in a document entitled “Wind Turbine Operation & Maintenance based on Condition Monitoring WT-Ω” by T. W. Verbruggen published by ECN Wind Energy, April 2003 (document number ECN-C-03-047).
Two of the more common CBM techniques are vibration-based monitoring and fluid-based monitoring. Vibration-based monitoring analyzes measured vibration of one or more components to estimate the condition and/or performance of wind turbine components. In a typical vibration-based monitoring system, position transducers are used for low frequency monitoring, velocity sensors are used for middle frequency monitoring, accelerometers are used for high frequency monitoring and spectral emitted energy (SEE) sensors are used for very high frequency monitoring. Thus, a typical-vibration monitoring system includes multiple types of sensors with multiple monitoring algorithms, which can be complex and costly.
Fluid-based monitoring typically involves taking samples of fluids, for example, hydraulic oil or lubrication oil, for analysis to determine whether a component has experienced excessive wear. However, fluid-based monitoring provides only limited information related to the condition of wind turbine components. Thus, existing condition based monitoring systems are complex and/or provide limited information.